This invention relates generally to adaptive signal processing structures for communication systems, and more particularly, the invention relates to an adaptive receiver structure that may be used to extract an information sequence associated with a wireless subscriber from a composite received signal. The composite received signal may include components of coded information sequences generated by multiple subscribers, additive ambient noise and effects of channel distortion.
Without limiting the scope of the invention, its background is described in connection with code division multiple access telecommunication devices and systems, as an example.
Heretofore, in this field, a user using a wireless handset transmits information from the handset to a base station. In commercial applications the wireless handset is most commonly a cellular phone or a personal communication system (PCS) phone. In military and other applications involving wireless transmission, the wireless handset may be generally be any mobile radio apparatus such as a spread spectrum transceiver or a mobile satellite terminal. A communication protocol used to transmit and receive wireless signals between the wireless handset and the base station is called an air interface. The air interface is typically agreed upon by an international standards committee.
Base stations generally include infrastructure equipment connected to a telephone network via a switching architecture. The base station processing circuits transmit and receive wireless signals to and from a set of wireless subscribers using an air interface protocol. In current commercial applications, for example, the base station is often deployed by a telephone company to pass cellular or PCS wireless traffic using one or more air interface standards. Other common air interface standards include analog service, time division multiple access (TDMA) and code division multiple access (CDMA). The most common analog air interface is known as advanced mobile phone service (AMPS). The most common TDMA air interfaces are IS-136 in the United States and Japan, and Global System Mobile (GSM) in Europe.
The most common CDMA air interface is called IS-95. New standards continue to emerge, especially as PCS becomes more prevalent. Also, many proprietary systems and military systems are also deployed. A wireless infrastructure is commonly created using a plurality of base stations connected via land lines (or microwave links) to a telephone network. A given base station analyzes the power in a given received signal to ensure it processes only the calls of those wireless subscribers closest to the given base station. Peer base stations may compare measurements to make a determination as to which base station will handle a given call at a given moment. When a subscriber travels from the coverage area of one base station to another, the base station currently processing the call is said to xe2x80x9chand the call offxe2x80x9d to the base station which will next handle the call.
Multi-user interference suppression algorithms make use of the properties of the multi-user interference in order to suppress errors due to other user""s signals which appear as special type of noise with known properties. These algorithms require the conversion of large matrices to jointly estimate the subscriber signals at once. A large matrix problem is formulated and all of the multiple user""s data signals are jointly estimated. This approach provides a benchmark for quality, but is too costly to implement in real time using modern digital signal processor technology.
It has been found, however, that the present methods for reducing the channel noise fail to correct for the additive ambient noise caused by multiple access interference (MAI) in CDMA systems. Due to MAI, the number of subscribers that can be accommodated by a CDMA base station is greatly limited. MAI is the noise created by the coded signals transmitted by all but a designated subscriber. The CDMA receiver must separate the designated signal from the MAI created by all the other users.
The present inventors have recognized that a significant problem of current methods for noise reduction is the high cost of the systems. For example, multiuser detectors make use of the fact that the base stations have knowledge of the spreading codes of the interfering signals to estimate the number of signals received concurrently at the base station. While the multiuser detector approach may lead to very high performance, it is extremely costly because large matrices must be processed to determine all of the interrelated and coded signal information. The problem is compounded when the effects of multi-path fading channels are taken into account.
An alternative form of multiuser detection known as multiple access interference suppression has been proposed. For example an MMSE multiple access interference suppression system is described in L. Zhu et. al., xe2x80x9cAdaptive interference suppression for direct sequence CDMA over severely time-varying channels,xe2x80x9d IEEE Globecom 1997 (henceforth the xe2x80x9cZhu referencexe2x80x9d). This type of objective function is known as decision-oriented because the receiver decides which symbol was sent and computes an error. In practice, however, an adaptive filter""s tap weights is adjusted to reduce the mean square error between the filter output and a set of constellation points. The recursive least squares algorithms, however, are also known to be very expensive in terms of cost of implementation and have known stability problems. Also, since these methods rely on past decisions generated by the receiver, the method breaks down when the signal conditions are unfavorable and too low of a number of decisions are erroneous for the receiver to lock onto the signal.
Another attempt to address the problem of MAI has been to apply a modulus restoration algorithm to achieve multiuser detection. Such a scheme is described in W. Lee, et. al, xe2x80x9cConstant modulus algorithm for blind multiuser detection,xe2x80x9d IEEE Spread Spectrum Communications Workshop, 1996. Multiuser detection is performed by using a bank of modulus restoration adaptive filters. The method proposed in the Lee reference has the advantage of requiring fewer computations than competing multiuser detectors, however, it has the disadvantage of a slow convergence rate and poor steady-state behavior when compared to the more expensive matrix-based and multiuser detectors.
The present inventors recognized that a problem with the use of modulus restoration adaptive filters is that it requires, a priori, information regarding signal and channel parameters in order to set a step size parameter used by the constant modulus algorithm. Hence, while the algorithm may be made to perform well in a simulated environment where this information is known, the method will not function properly in a time-varying and unknown environment as encountered by signal processors operating within mobile cellular and PCS air interface equipment.
The present inventors have also recognized that one way to improve the performance of modulus restoration adaptive filters would be to use Recursive Least Squares (RLS) based adaptive filter to perform modulus restorative adaptive filtering. RLS-based adaptive filters do not require a step-size parameter and converge more rapidly than the Least Mean Squares (LMS) based approach. RLS-based filters, however, are expensive to implement in real time and do not guarantee stability. Moreover, fast RLS algorithms involve underlying data Toeplitz matrices. If these algorithms are attempted chip-rate sampled CDMA data streams, the stability problems worsen.
Methods have also been advanced to adapt an adaptive filter to minimize a constant modulus objective function using a nonlinear optimization algorithm. The nonlinear optimization algorithm is made to function with time-varying data by segmenting the input data into blocks. Multiple iterations of the algorithm may be performed on each block, and an adaptive step size is calculated at each iteration without the need for unavailable a priori information.
Moreover, algorithms may be constructed which are guaranteed to update the weights to reduce the error function at each iteration. These algorithms, however, use Toeplitz matrices and are more useful for TDMA and related environments where only a single user makes use of the channel at any given instant (see, e.g., xe2x80x9cBlock Shanno Constant Modulus Algorithm for Wireless Equalizations,: Wang and Dowling, Proceedings of the IEEE ICASSP 1996; xe2x80x9cStochastic conjugate gradient constant modulus blind equalizer for wireless communications,xe2x80x9d Wang and Dowling, Proceedings of the IEEE ICC 1996.)
The present invention solves these and other problems by providing low cost and efficient methods and apparatus to restore a received signal which has been corrupted by a multipath fading channel, additive Gaussian noise, and/or MAI. While the preferred embodiments focus on restoration of signals associated with TDMA and CDMA wireless communications systems, the inventive methods and apparatus may be applied to other types of systems, for example wireline systems to include twisted pair, coaxial cables, and fiber channels. An important aspect of the present invention is a quasi-Newton adaptive filter structure used to perform modulus restoration of a received signal. This filter may be used to perform both channel equalization in TDMA systems and multiple access interference suppression in CDMA systems. The inventive quasi-Newton filter may also be applied to non-communication system related problems which involve the minimization of a cost function for which a gradient and a maximum a posteriori (MAP) or a pseudo-MAP step size may be computed.
The invention solves the prior art problem of high cost CDMA base stations by replacing the need to perform costly matrix-based multiuser detection or MMSE based multiple access interference suppression with a much more economical modulus restoration approach. The approach of the present invention has a computational requirement similar to the conventional RAKE receiver while providing significant performance gains normally associated with the more expensive multiuser detectors.
The invention also solves the problem of needing to make engineering trade-offs when deciding between a low-cost, slow converging constant modulus equalizer or a much more expensive but faster converging constant modulus equalizer. That is, the invention provides a low cost but high performance constant modulus equalizer structure operative to restore both TDMA, CDMA and related signals after having been corrupted by channel distortions and additive noise.
The invention is enabled by a novel quasi-Newton adaptive filter structure and method which is related to a generalized form of conjugate gradient minimization scheme as proposed in the Wang reference. However, the method of the Wang reference is designed for TDMA data and thereby uses a Toeplitz data matrix. If such an approach is applied to CDMA data, ill conditioning resulting in large errors results. Also, the computation increases quadratically with the number of filter taps since much work is wasted processing non-symbol related information. Even when the data blocks are redesigned to support CDMA processing in accordance with the present invention, when the Wang reference is applied to CDMA signals, an erroneously recovered signal constellation results. This is because the Wang reference teaches to drive the error below a threshold, and when this is done with CDMA data, the recovered signal constellation smears out along a unit circle. The present algorithm employs an early-stopping strategy of advancing at most a fixed number of iterations each update in order to correct this deficiency and to produce a working CDMA system. These two distinctions produce a constant modulus filter which reduces computation by an order of magnitude and produces a higher accuracy output signal. Beside these advancements over the Wang reference discussed hereinabove, the present invention teaches a method of perform multiple access interference suppression in CDMA systems.
The present invention also includes a communications receiver having an adaptive filter adapted to minimize an error function, wherein the error function is calculated using differences between output blocks generated by the adaptive filter. The output blocks will generally correspond to repeated blocks inherent in a communications protocol used by the CDMA receiver.